Information about online customer buying behavior and decision making can now be used to improve offline as well as online marketing. With web analytics, companies can test alternative sales messages, offers and promotions on their e-commerce websites, and then use the most successful message, offer or promotion in offline media (such as print publications or radio) and offline sales processes (such as direct sales, telesales or retail).

Jim Sterne, Chairman of the Web Analytics Association, has been promoting this approach in interviews, webinars and conference presentations since 2006, when he noted that a few companies were just beginning to get “insights coming out of their web analytics tools that were powerful enough to impact decisions the corporation made about offline marketing.”

The approach works like this:

People search online for information on just about every product or service that they are thinking about buying, whether they intend to buy it online or offline. This means that companies can reach people online, even if their purchases will be offline.

People’s responses to online information are very similar to their responses to the same information when it’s provided offline. This means that their responses to online information are excellent predictors of their responses to the same information provided offline.

The information presented to them online can include choices between two or more alternatives, such as a “buy 1 get 2″ offer vs. a “50% off” offer. Even though these offers are mathematically the same, one offer will be selected by customers much more often than the other. Web analytics tools can identify the more popular offer from the customers’ online choices.

For every group of alternatives, the most popular alternative online turns out to be the most compelling offline as well. The company should use that alternative online and offline.

The most popular alternative then becomes the “control.” Other alternatives can be tested against it to find an even more popular and compelling offer.

In addition to testing alternative offers, companies have been using the Internet to test alternatives in marketing strategy, creative approaches, positioning, pricing and promotions. Online testing is quick. Hundreds or thousands of alternatives can be generated automatically and tested thoroughly in 24 hours, if a website has enough traffic. Web analytics tools can identify the most popular alternatives in minutes.

When I discussed this approach with Jim Young, Market Research Manager with BrandSolutions, he suggested that the most efficient and customer-friendly method for determining the optimum set of product features to meet customer preferences and maximize profitability, is conjoint analysis. This analytical technique obviates the need to test every combination of features, which would be daunting for customers to sort through.

With conjoint analysis, customers are asked to make price/feature tradeoff decisions as part of the product selection process on an existing e-commerce website, or via online surveys. In fact, the conjoint analysis solution works for situations where there are many variations in any of the alternatives in marketing strategies, creative approaches, positioning, pricing or promotions.

By using conjoint analysis in conjunction with web analytics tools, the most popular and profitable alternatives can be identified quickly, and they can be put to productive use online and offline immediately.